Files
ceres-solver/internal/ceres/program.h
T
Keir Mierle f44907f702 Compute the gradient if requested in the evaluator
This extends the Evaluator interface to support evaluating the
gradient in addition to the residuals and jacobian, if requested.

   bool Evaluate(const double* state,
                 double* cost,
                 double* residuals,
                 double* gradient,  <----------- NEW
                 SparseMatrix* jacobian) = 0;

The ProgramEvaluator is extended to support the new gradient
evaluation. This required some gymnastics around the block
evaluate preparer, which now contains a scratch evaluate preparer
for the case that no jacobian is requested but the gradient is.

Gradient evaluation is a prerequisite for the planned suite of
first order methods, including nonlinear conjugate gradient,
CG_DESCENT, L-BFGS, trust region with line search, and more.

This also considerably refactors the evaluator_test to make it
shorter and check the results for all combinations of the optional
parameters [residuals, gradient, jacobian].

Change-Id: Ic7d0fec028dc5ffebc08ee079ad04eeaf6e02582
2012-07-11 09:44:45 -07:00

135 lines
5.7 KiB
C++

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
// * Redistributions in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
// * Neither the name of Google Inc. nor the names of its contributors may be
// used to endorse or promote products derived from this software without
// specific prior written permission.
//
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
// POSSIBILITY OF SUCH DAMAGE.
//
// Author: keir@google.com (Keir Mierle)
#ifndef CERES_INTERNAL_PROGRAM_H_
#define CERES_INTERNAL_PROGRAM_H_
#include <vector>
#include "ceres/internal/port.h"
namespace ceres {
namespace internal {
class ParameterBlock;
class ProblemImpl;
class ResidualBlock;
// A nonlinear least squares optimization problem. This is different from the
// similarly-named "Problem" object, which offers a mutation interface for
// adding and modifying parameters and residuals. The Program contains the core
// part of the Problem, which is the parameters and the residuals, stored in a
// particular ordering. The ordering is critical, since it defines the mapping
// between (residual, parameter) pairs and a position in the jacobian of the
// objective function. Various parts of Ceres transform one Program into
// another; for example, the first stage of solving involves stripping all
// constant parameters and residuals. This is in contrast with Problem, which is
// not built for transformation.
class Program {
public:
Program();
explicit Program(const Program& program);
// The ordered parameter and residual blocks for the program.
const vector<ParameterBlock*>& parameter_blocks() const;
const vector<ResidualBlock*>& residual_blocks() const;
vector<ParameterBlock*>* mutable_parameter_blocks();
vector<ResidualBlock*>* mutable_residual_blocks();
// Serialize to/from the program and update states.
//
// NOTE: Setting the state of a parameter block can trigger the
// computation of the Jacobian of its local parameterization. If
// this computation fails for some reason, then this method returns
// false and the state of the parameter blocks cannot be trusted.
bool StateVectorToParameterBlocks(const double *state);
void ParameterBlocksToStateVector(double *state) const;
// Copy internal state to the user's parameters.
void CopyParameterBlockStateToUserState();
// Set the parameter block pointers to the user pointers. Since this
// runs parameter block set state internally, which may call local
// parameterizations, this can fail. False is returned on failure.
bool SetParameterBlockStatePtrsToUserStatePtrs();
// Update a state vector for the program given a delta.
bool Plus(const double* state,
const double* delta,
double* state_plus_delta) const;
// Set the parameter indices and offsets. This permits mapping backward
// from a ParameterBlock* to an index in the parameter_blocks() vector. For
// any parameter block p, after calling SetParameterOffsetsAndIndex(), it
// is true that
//
// parameter_blocks()[p->index()] == p
//
// If a parameter appears in a residual but not in the parameter block, then
// it will have an index of -1.
//
// This also updates p->state_offset() and p->delta_offset(), which are the
// position of the parameter in the state and delta vector respectively.
void SetParameterOffsetsAndIndex();
// See problem.h for what these do.
int NumParameterBlocks() const;
int NumParameters() const;
int NumEffectiveParameters() const;
int NumResidualBlocks() const;
int NumResiduals() const;
int MaxScratchDoublesNeededForEvaluate() const;
int MaxDerivativesPerResidualBlock() const;
int MaxParametersPerResidualBlock() const;
int MaxResidualsPerResidualBlock() const;
// Evaluate the cost and maybe the residuals for the program. If residuals is
// NULL, then residuals are not calculated. If the jacobian is needed, instead
// use the various evaluators (e.g. dense_evaluator.h).
//
// This is a trivial implementation of evaluate not intended for use in the
// core solving loop. The other evaluators, which support constructing the
// jacobian in addition to the cost and residuals, are considerably
// complicated by the need to construct the jacobian.
bool Evaluate(double* cost, double* residuals);
private:
// The Program does not own the ParameterBlock or ResidualBlock objects.
vector<ParameterBlock*> parameter_blocks_;
vector<ResidualBlock*> residual_blocks_;
friend class ProblemImpl;
};
} // namespace internal
} // namespace ceres
#endif // CERES_INTERNAL_PROGRAM_H_